MVMOO: mixed variable multi-objective optimisation

DOI10.1007/S10898-021-01052-9zbMath1475.90094OpenAlexW3177619992MaRDI QIDQ2046315

Thomas W. Chamberlain, Jamie A. Manson, Richard A. Bourne

Publication date: 17 August 2021

Published in: Journal of Global Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10898-021-01052-9

zbMATH Keywords

hypervolumeglobal optimisationmulti-objectiveBayesian optimisationmixed variable

Mathematics Subject Classification ID

Mixed integer programming (90C11) Multi-objective and goal programming (90C29)

Uses Software

• SciPy
• Python
• TensorFlow
• GPflow
• DFVLR-SQP
• jMetalPy

Cites Work

• Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm
• A family of embedded Runge-Kutta formulae
• Expected improvement for expensive optimization: a review
• Computing 3-D Expected Hypervolume Improvement and Related Integrals in Asymptotically Optimal Time
• A tutorial on multiobjective optimization: fundamentals and evolutionary methods
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